Can You Predict a Driver’s Success from their Rookie Year Stats?

Now that the season is over, it’s time to look through the statistics from the year. One big story this year was Danica Patrick’s rookie season in Sprint Cup. She didn’t set the world on fire: One top ten, one pole, five laps led and only thirteen lead lap finishes put her in 27th place for the season.

Tony Stewart, when asked about Danica’s rookie year, said that he saw ‘potential’. Potential tends to be an ephemeral thing and numbers geeks like me strive to put a quantitative slant on everything, so I thought I’d look at the numbers and see if there was anything we could glean from comparing different driver’s rookie year stats. With thanks again to the folks at racing-reference.info for the numbers, here goes.

I didn’t include stats like average starting position or poles because, frankly, you don’t get a championship that way. I focused on how drivers finished. The graph below shows the percentage wins, top five and top tens for a number of drivers, ranging from champions to drivers still proving themselves and, yes, two of our rookie-of-the-year competitors.

I think it is fair to conclude that the best drivers in the series – the multi-time champions like Johnson and Stewart – were just good from day one. Finishing almost 60 percent of your races in the top 10 in your first year is pretty darned impressive. The guys who looked like champions in their first year usually became champions (or came pretty close).

But the converse doesn’t hold. A slow start doesn’t preclude the possibility of your becoming a champion.

If you look at the graph above to find a driver whose rookie year is comparable to Danica’s, you inevitably land on Brad Kezelowski. His rookie stats weren’t that different than Danica’s. She had one top-ten, he had two. Neither had any top fives or wins. They both had a pole.

So maybe there’s something that average statistics, like top tens and top fives don’t tell you.

Digging Deeper: Histograms

A histogram plots the frequency of occurrence – for example, how many times a driver finished within each particular range of finishing positions.

I chose this kind of analysis because it’s the next step up from an average finishing position. You can take two drivers with the same average, and one could finish 17th every race, while the other alternated between winning and crashing out in the first lap. Someone once told me that ‘averages hide a multitude of sins’ .

I broke the finishing positions into five-position segments, but I broke out wins separately. The histogram to the right shows Jimmie Johnson’s finishes for his rookie (2002) season. The bar corresponding to ’35’ on the chart at right shows that Jimmie Johnson had four finishes between 35th and 39th that year. The bar corresponding to ‘5’ shows that Jimmie had 14 finishes between P5 and P9. Johnson had an average finish of 13.5 and finished 5th in the standings that year.

The histogram for Tony Stewart’s rookie season (1999) looks a little different than Johnson’s in the details, but (like Jimmies) it’s skewed to the right-hand side of the plot (meaning more good finishes). Stewart had an average finish of 10.3 and finished 4th in the standings.

And then we come to Kezelowski, who had an average finish of 22.4 and finished 25th in the standings. Unlike Johnson and Stewart, who have significant bars for top fives and wins, there are no bars for Kezelowski. He had a few bad finishes, but he consistently ran between 25th and 10th, with more of the finishes being on the higher end of that range.

Which brings us to Danica. Even though she finished in 27th place (only two behind Brad in his rookie year), the statistical distribution of her finishes looks much different than Keselowski’s.

The mode of a group of numbers is the number that appears most often. It’s the most probable outcome – and the highest bar in these histograms. Brad has a pretty even spread between 30-10, but Danica has a pretty significant peak at the 25-29th place finishing positions. She had a lot of finishes in the 25-29, while Brad was almost equally likely to finish 10th as 30th.

How Drivers Change

The big question, of course, isn’t how anyone did last year – it’s how they’re going to do in the future. If there were some magical algorithm that allowed an owner to predict that, if they put three years of development into a driver, he or she would pay off, they’d have no problems deciding who to keep and who to let go.

I was curious about how drivers changed. If you start off good, there isn’t much room for improvement, right?

This histogram compares Jimmie Johnson’s finishes in 2002 with those of this year. He’s got fewer bad finishes and increased the number of wins, top 5s and top 10s. Bad finishes are tricky because in a sport like this, you can get a bad finish through no fault of your own if you get caught up in someone else’s accident. I haven’t looked at it in detail, but my first glance suggests many of the bad finishes for drivers who don’t have a lot of bad finishes are at the short tracks and the superspeedways, or they’re due to equipment malfunctioning, like a motor or transmission giving out.

What about Brad, whose rookie year wasn’t quite as promising?

This histogram compares Brad’s rookie year, 2010 with his championship year, 2012. Look at the difference in finishes in just two years. With the exception of a very few bad finishes (one was Daytona) every finish was 19th place and up. What happened in those two years? Some experience. A new crew chief with whom Kezelowski seems to have really bonded.

What Does it All Mean?

If a driver starts off with a slew of top 10s in his first year, the chances are very high that driver will continue to run at the top as his or her career progresses. You cannot, however, make the converse argument: a driver with a weak rookie year may — or may not — become competitive. We’ve seen some good drivers from other series come to NASCAR and struggle.

There are many factors that go into winning: you have to have most of them to run well. Sometimes something like changing crew chiefs, owners or even being in the final year of a contract will radically change how a driver runs. Look at Joey Logano when he moved to Penske, or Matt Kenseth when he moved to Gibbs.

Now… that isn’t to say that there aren’t some clues that might tell you whether a driver is destined for greatness or mid-pack purgatory. We’ll dive deeper into the data next time.

4 thoughts on “Can You Predict a Driver’s Success from their Rookie Year Stats?”

I watched Gordon many many yrs. ago @ the magic mile, he was driving a pure white car an his sponsor was “Baby Ruth”, I believe, if my o’l brain servers me correctly, the car # was 5. anyway, I mentioned to my son…Dave, look up this driver in the # 5 car, who ever he is he’s one heck of a driver. Well that was many many yrs. ago…”TODAY 2014, WELL, I NEED SAY MORE”1

Maybe it’s just an o’l man blow’n smoke but the way I felt about Gordon yrs. ago an his future is a feel’n I’m have’n about Lagano also, I can’t put finger on it yet, but something tells me he’s gonna be the “dark horse” for the chase this yr., maybe not the champ when seasons over, but I’m think’n pretty dam close. Last leg of this yr. is going ta be very interesting. Needs more experience, but a very quick study. Well see, right….Love NASCAR, LOVE RACING ! JUST PLEASE DON’T TURN THESE BUSES INTO GO CARTS ON STEROIDS, WE ALREADY HAVE THAT IN INDY CARS. KEEP THE BUSSES BUSSES AN THE GO CARTS GO CARTS.

It occurred to me today, 08/26, you posted wrong info. on # of Gordon’s “Baby Ruth” car. It was not # 5, it was actually # 1, again, many many yrs. ago, when Gordon was only a puppy. The o’l brain
is still somewhat functional. when I can’t remember to visit this fabulous web site, then I’ll take off my helmet an “walk” away.